from sklearn_benchmarks.reporting.hp_match import HpMatchReporting
import pandas as pd
pd.set_option('display.max_colwidth', None)
pd.set_option('display.max_columns', None)
pd.set_option('display.max_rows', None)
reporting = HpMatchReporting(other_library="sklearnex", config="config.yml", log_scale=True)
reporting.make_report()
We assume here there is a perfect match between the hyperparameters of both librairies. For a given set of parameters and a given dataset, we compute the speedup
time scikit-learn / time sklearnex. For instance, a speedup of 2 means that sklearnex is twice as fast as scikit-learn for a given set of parameters and a given dataset.
KNeighborsClassifier_brute_force¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=brute.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 0.024 | 100000 | 1000 | 100 | 1.945158 | 0.174170 | NaN | 0.000411 | 0.001945 | brute | -1 | 1 | 0.663 | 0.173001 | 0.003892 | 0.687 | 11.243621 | 11.246466 |
| 4 | KNeighborsClassifier_brute_force | predict | 0.015 | 100000 | 1000 | 100 | 2.759015 | 0.022848 | NaN | 0.000290 | 0.002759 | brute | -1 | 5 | 0.757 | 0.176017 | 0.005928 | 0.742 | 15.674675 | 15.683563 |
| 7 | KNeighborsClassifier_brute_force | predict | 0.007 | 100000 | 1000 | 100 | 2.060653 | 0.033896 | NaN | 0.000388 | 0.002061 | brute | 1 | 100 | 0.882 | 0.207801 | 0.001673 | 0.875 | 9.916474 | 9.916795 |
| 8 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.033698 | 0.013977 | NaN | 0.000024 | 0.033698 | brute | 1 | 100 | 1.000 | 0.008603 | 0.000278 | 0.000 | 3.916920 | 3.918967 |
| 10 | KNeighborsClassifier_brute_force | predict | 0.007 | 100000 | 1000 | 100 | 2.786869 | 0.043162 | NaN | 0.000287 | 0.002787 | brute | -1 | 100 | 0.882 | 0.208362 | 0.000498 | 0.875 | 13.375151 | 13.375189 |
| 11 | KNeighborsClassifier_brute_force | predict | 1.000 | 100000 | 1 | 100 | 0.022921 | 0.002096 | NaN | 0.000035 | 0.022921 | brute | -1 | 100 | 1.000 | 0.008707 | 0.000804 | 0.000 | 2.632306 | 2.643510 |
| 13 | KNeighborsClassifier_brute_force | predict | 0.015 | 100000 | 1000 | 100 | 2.021048 | 0.007167 | NaN | 0.000396 | 0.002021 | brute | 1 | 5 | 0.757 | 0.172025 | 0.000248 | 0.742 | 11.748590 | 11.748602 |
| 16 | KNeighborsClassifier_brute_force | predict | 0.024 | 100000 | 1000 | 100 | 1.160968 | 0.002671 | NaN | 0.000689 | 0.001161 | brute | 1 | 1 | 0.663 | 0.172713 | 0.000432 | 0.687 | 6.721949 | 6.721970 |
| 19 | KNeighborsClassifier_brute_force | predict | 0.071 | 100000 | 1000 | 2 | 1.752716 | 0.023652 | NaN | 0.000009 | 0.001753 | brute | -1 | 1 | 0.896 | 0.025569 | 0.000230 | 0.967 | 68.548700 | 68.551473 |
| 22 | KNeighborsClassifier_brute_force | predict | 0.052 | 100000 | 1000 | 2 | 2.641044 | 0.014811 | NaN | 0.000006 | 0.002641 | brute | -1 | 5 | 0.922 | 0.026547 | 0.000071 | 0.974 | 99.485543 | 99.485902 |
| 25 | KNeighborsClassifier_brute_force | predict | 0.046 | 100000 | 1000 | 2 | 1.954314 | 0.002365 | NaN | 0.000008 | 0.001954 | brute | 1 | 100 | 0.929 | 0.059959 | 0.001892 | 0.975 | 32.594196 | 32.610421 |
| 28 | KNeighborsClassifier_brute_force | predict | 0.046 | 100000 | 1000 | 2 | 2.651842 | 0.023051 | NaN | 0.000006 | 0.002652 | brute | -1 | 100 | 0.929 | 0.059574 | 0.000147 | 0.975 | 44.513100 | 44.513236 |
| 31 | KNeighborsClassifier_brute_force | predict | 0.052 | 100000 | 1000 | 2 | 1.932948 | 0.003562 | NaN | 0.000008 | 0.001933 | brute | 1 | 5 | 0.922 | 0.026996 | 0.000936 | 0.974 | 71.601608 | 71.644610 |
| 34 | KNeighborsClassifier_brute_force | predict | 0.071 | 100000 | 1000 | 2 | 1.060468 | 0.008314 | NaN | 0.000015 | 0.001060 | brute | 1 | 1 | 0.896 | 0.025551 | 0.000073 | 0.967 | 41.504331 | 41.504498 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.262 | 0.0 | -1 | 1 | 0.050 | 0.005 | 0.221 | 0.222 | See | See |
| 3 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.240 | 0.0 | -1 | 5 | 0.048 | 0.001 | 0.230 | 0.230 | See | See |
| 6 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.233 | 0.0 | 1 | 100 | 0.048 | 0.000 | 0.230 | 0.230 | See | See |
| 9 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.014 | 0.005 | 5.749 | 0.0 | -1 | 100 | 0.048 | 0.001 | 0.292 | 0.292 | See | See |
| 12 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.185 | 0.0 | 1 | 5 | 0.048 | 0.000 | 0.231 | 0.231 | See | See |
| 15 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 100 | 0.011 | 0.000 | 7.163 | 0.0 | 1 | 1 | 0.049 | 0.000 | 0.230 | 0.230 | See | See |
| 18 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.372 | 0.0 | -1 | 1 | 0.008 | 0.000 | 0.524 | 0.524 | See | See |
| 21 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.376 | 0.0 | -1 | 5 | 0.008 | 0.000 | 0.509 | 0.509 | See | See |
| 24 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.377 | 0.0 | 1 | 100 | 0.008 | 0.000 | 0.513 | 0.513 | See | See |
| 27 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.378 | 0.0 | -1 | 100 | 0.008 | 0.000 | 0.511 | 0.511 | See | See |
| 30 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.377 | 0.0 | 1 | 5 | 0.008 | 0.000 | 0.506 | 0.506 | See | See |
| 33 | KNeighborsClassifier_brute_force | fit | 100000 | 100000 | 2 | 0.004 | 0.000 | 0.375 | 0.0 | 1 | 1 | 0.008 | 0.000 | 0.516 | 0.516 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.945 | 0.174 | 0.000 | 0.002 | -1 | 1 | 0.173 | 0.004 | 11.244 | 11.246 | See | See |
| 2 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.003 | 0.000 | 0.023 | -1 | 1 | 0.008 | 0.000 | 2.701 | 2.701 | See | See |
| 4 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.759 | 0.023 | 0.000 | 0.003 | -1 | 5 | 0.176 | 0.006 | 15.675 | 15.684 | See | See |
| 5 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.003 | 0.000 | 0.023 | -1 | 5 | 0.008 | 0.000 | 2.781 | 2.782 | See | See |
| 7 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.061 | 0.034 | 0.000 | 0.002 | 1 | 100 | 0.208 | 0.002 | 9.916 | 9.917 | See | See |
| 8 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.034 | 0.014 | 0.000 | 0.034 | 1 | 100 | 0.009 | 0.000 | 3.917 | 3.919 | See | See |
| 10 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.787 | 0.043 | 0.000 | 0.003 | -1 | 100 | 0.208 | 0.000 | 13.375 | 13.375 | See | See |
| 11 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.023 | 0.002 | 0.000 | 0.023 | -1 | 100 | 0.009 | 0.001 | 2.632 | 2.644 | See | See |
| 13 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 2.021 | 0.007 | 0.000 | 0.002 | 1 | 5 | 0.172 | 0.000 | 11.749 | 11.749 | See | See |
| 14 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.000 | 0.000 | 0.019 | 1 | 5 | 0.009 | 0.000 | 2.233 | 2.235 | See | See |
| 16 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 100 | 1.161 | 0.003 | 0.001 | 0.001 | 1 | 1 | 0.173 | 0.000 | 6.722 | 6.722 | See | See |
| 17 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 100 | 0.019 | 0.002 | 0.000 | 0.019 | 1 | 1 | 0.009 | 0.000 | 2.267 | 2.269 | See | See |
| 19 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.753 | 0.024 | 0.000 | 0.002 | -1 | 1 | 0.026 | 0.000 | 68.549 | 68.551 | See | See |
| 20 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.006 | 0.004 | 0.000 | 0.006 | -1 | 1 | 0.001 | 0.000 | 9.260 | 9.280 | See | See |
| 22 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.641 | 0.015 | 0.000 | 0.003 | -1 | 5 | 0.027 | 0.000 | 99.486 | 99.486 | See | See |
| 23 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.007 | 0.005 | 0.000 | 0.007 | -1 | 5 | 0.001 | 0.000 | 11.634 | 11.664 | See | See |
| 25 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.954 | 0.002 | 0.000 | 0.002 | 1 | 100 | 0.060 | 0.002 | 32.594 | 32.610 | See | See |
| 26 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 100 | 0.001 | 0.000 | 4.107 | 4.119 | See | See |
| 28 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 2.652 | 0.023 | 0.000 | 0.003 | -1 | 100 | 0.060 | 0.000 | 44.513 | 44.513 | See | See |
| 29 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.008 | 0.002 | 0.000 | 0.008 | -1 | 100 | 0.001 | 0.000 | 10.810 | 10.864 | See | See |
| 31 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.933 | 0.004 | 0.000 | 0.002 | 1 | 5 | 0.027 | 0.001 | 71.602 | 71.645 | See | See |
| 32 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.003 | 0.000 | 0.000 | 0.003 | 1 | 5 | 0.001 | 0.000 | 4.528 | 4.546 | See | See |
| 34 | KNeighborsClassifier_brute_force | predict | 100000 | 1000 | 2 | 1.060 | 0.008 | 0.000 | 0.001 | 1 | 1 | 0.026 | 0.000 | 41.504 | 41.504 | See | See |
| 35 | KNeighborsClassifier_brute_force | predict | 100000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 1 | 0.001 | 0.000 | 2.876 | 2.888 | See | See |
KNeighborsClassifier_kd_tree¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=kd_tree.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | n_jobs | n_neighbors | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 0.019 | 1000000 | 1000 | 10 | 0.846699 | 1.024024 | NaN | 0.000094 | 0.000847 | kd_tree | -1 | 1 | 0.929 | 0.125995 | 0.003272 | 0.910 | 6.720102 | 6.722368 |
| 4 | KNeighborsClassifier_kd_tree | predict | 0.005 | 1000000 | 1000 | 10 | 1.084310 | 0.367576 | NaN | 0.000074 | 0.001084 | kd_tree | -1 | 5 | 0.946 | 0.213829 | 0.003646 | 0.941 | 5.070915 | 5.071652 |
| 7 | KNeighborsClassifier_kd_tree | predict | 0.011 | 1000000 | 1000 | 10 | 5.655300 | 0.495737 | NaN | 0.000014 | 0.005655 | kd_tree | 1 | 100 | 0.951 | 0.649424 | 0.015273 | 0.940 | 8.708174 | 8.710582 |
| 10 | KNeighborsClassifier_kd_tree | predict | 0.011 | 1000000 | 1000 | 10 | 3.315664 | 0.347322 | NaN | 0.000024 | 0.003316 | kd_tree | -1 | 100 | 0.951 | 0.637073 | 0.010695 | 0.940 | 5.204530 | 5.205263 |
| 13 | KNeighborsClassifier_kd_tree | predict | 0.005 | 1000000 | 1000 | 10 | 1.803258 | 0.411965 | NaN | 0.000044 | 0.001803 | kd_tree | 1 | 5 | 0.946 | 0.223114 | 0.003650 | 0.941 | 8.082243 | 8.083324 |
| 16 | KNeighborsClassifier_kd_tree | predict | 0.019 | 1000000 | 1000 | 10 | 0.927696 | 0.169602 | NaN | 0.000086 | 0.000928 | kd_tree | 1 | 1 | 0.929 | 0.119940 | 0.001786 | 0.910 | 7.734659 | 7.735517 |
| 19 | KNeighborsClassifier_kd_tree | predict | 0.012 | 1000 | 1000 | 2 | 0.026077 | 0.013312 | NaN | 0.000614 | 0.000026 | kd_tree | -1 | 1 | 0.891 | 0.000398 | 0.000045 | 0.879 | 65.453182 | 65.863322 |
| 22 | KNeighborsClassifier_kd_tree | predict | 0.006 | 1000 | 1000 | 2 | 0.023598 | 0.000617 | NaN | 0.000678 | 0.000024 | kd_tree | -1 | 5 | 0.911 | 0.000641 | 0.000025 | 0.905 | 36.819075 | 36.847445 |
| 25 | KNeighborsClassifier_kd_tree | predict | 0.023 | 1000 | 1000 | 2 | 0.034779 | 0.004690 | NaN | 0.000460 | 0.000035 | kd_tree | 1 | 100 | 0.894 | 0.004482 | 0.000028 | 0.917 | 7.760221 | 7.760376 |
| 28 | KNeighborsClassifier_kd_tree | predict | 0.023 | 1000 | 1000 | 2 | 0.037834 | 0.003823 | NaN | 0.000423 | 0.000038 | kd_tree | -1 | 100 | 0.894 | 0.005160 | 0.001467 | 0.917 | 7.332740 | 7.623220 |
| 31 | KNeighborsClassifier_kd_tree | predict | 0.006 | 1000 | 1000 | 2 | 0.020110 | 0.000135 | NaN | 0.000796 | 0.000020 | kd_tree | 1 | 5 | 0.911 | 0.000642 | 0.000031 | 0.905 | 31.317454 | 31.353569 |
| 34 | KNeighborsClassifier_kd_tree | predict | 0.012 | 1000 | 1000 | 2 | 0.018861 | 0.000117 | NaN | 0.000848 | 0.000019 | kd_tree | 1 | 1 | 0.891 | 0.000387 | 0.000025 | 0.879 | 48.782272 | 48.882440 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 2.947 | 0.034 | 0.027 | 0.0 | -1 | 1 | 0.818 | 0.091 | 3.604 | 3.626 | See | See |
| 3 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.620 | 0.053 | 0.022 | 0.0 | -1 | 5 | 0.766 | 0.013 | 4.725 | 4.726 | See | See |
| 6 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.718 | 0.060 | 0.022 | 0.0 | 1 | 100 | 0.759 | 0.004 | 4.897 | 4.897 | See | See |
| 9 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 4.086 | 0.072 | 0.020 | 0.0 | -1 | 100 | 0.755 | 0.010 | 5.411 | 5.412 | See | See |
| 12 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.800 | 0.048 | 0.021 | 0.0 | 1 | 5 | 0.771 | 0.011 | 4.929 | 4.929 | See | See |
| 15 | KNeighborsClassifier_kd_tree | fit | 1000000 | 1000000 | 10 | 3.860 | 0.070 | 0.021 | 0.0 | 1 | 1 | 0.757 | 0.015 | 5.100 | 5.100 | See | See |
| 18 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.001 | 0.016 | 0.0 | -1 | 1 | 0.003 | 0.002 | 0.332 | 0.374 | See | See |
| 21 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | -1 | 5 | 0.002 | 0.002 | 0.233 | 0.296 | See | See |
| 24 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | 1 | 100 | 0.001 | 0.001 | 0.457 | 0.555 | See | See |
| 27 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | -1 | 100 | 0.001 | 0.000 | 0.617 | 0.618 | See | See |
| 30 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | 1 | 5 | 0.001 | 0.000 | 0.623 | 0.625 | See | See |
| 33 | KNeighborsClassifier_kd_tree | fit | 1000 | 1000 | 2 | 0.001 | 0.000 | 0.031 | 0.0 | 1 | 1 | 0.001 | 0.000 | 0.664 | 0.664 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | n_jobs | n_neighbors | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.847 | 1.024 | 0.000 | 0.001 | -1 | 1 | 0.126 | 0.003 | 6.720 | 6.722 | See | See |
| 2 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.000 | 0.000 | 0.003 | -1 | 1 | 0.000 | 0.000 | 9.686 | 10.154 | See | See |
| 4 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.084 | 0.368 | 0.000 | 0.001 | -1 | 5 | 0.214 | 0.004 | 5.071 | 5.072 | See | See |
| 5 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.003 | 0.001 | 0.000 | 0.003 | -1 | 5 | 0.000 | 0.000 | 8.103 | 8.660 | See | See |
| 7 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 5.655 | 0.496 | 0.000 | 0.006 | 1 | 100 | 0.649 | 0.015 | 8.708 | 8.711 | See | See |
| 8 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.004 | 0.001 | 0.000 | 0.004 | 1 | 100 | 0.001 | 0.000 | 4.549 | 4.867 | See | See |
| 10 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 3.316 | 0.347 | 0.000 | 0.003 | -1 | 100 | 0.637 | 0.011 | 5.205 | 5.205 | See | See |
| 11 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.006 | 0.001 | 0.000 | 0.006 | -1 | 100 | 0.001 | 0.000 | 7.852 | 8.362 | See | See |
| 13 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 1.803 | 0.412 | 0.000 | 0.002 | 1 | 5 | 0.223 | 0.004 | 8.082 | 8.083 | See | See |
| 14 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.002 | 0.000 | 0.000 | 0.002 | 1 | 5 | 0.000 | 0.000 | 3.879 | 4.167 | See | See |
| 16 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1000 | 10 | 0.928 | 0.170 | 0.000 | 0.001 | 1 | 1 | 0.120 | 0.002 | 7.735 | 7.736 | See | See |
| 17 | KNeighborsClassifier_kd_tree | predict | 1000000 | 1 | 10 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 3.760 | 4.063 | See | See |
| 19 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.026 | 0.013 | 0.001 | 0.000 | -1 | 1 | 0.000 | 0.000 | 65.453 | 65.863 | See | See |
| 20 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 1 | 0.000 | 0.000 | 27.003 | 28.846 | See | See |
| 22 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.024 | 0.001 | 0.001 | 0.000 | -1 | 5 | 0.001 | 0.000 | 36.819 | 36.847 | See | See |
| 23 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 5 | 0.000 | 0.000 | 26.460 | 28.184 | See | See |
| 25 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.035 | 0.005 | 0.000 | 0.000 | 1 | 100 | 0.004 | 0.000 | 7.760 | 7.760 | See | See |
| 26 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 100 | 0.000 | 0.000 | 6.344 | 6.701 | See | See |
| 28 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.038 | 0.004 | 0.000 | 0.000 | -1 | 100 | 0.005 | 0.001 | 7.333 | 7.623 | See | See |
| 29 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.002 | 0.000 | 0.000 | 0.002 | -1 | 100 | 0.000 | 0.000 | 23.682 | 25.112 | See | See |
| 31 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.020 | 0.000 | 0.001 | 0.000 | 1 | 5 | 0.001 | 0.000 | 31.317 | 31.354 | See | See |
| 32 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 5 | 0.000 | 0.000 | 6.486 | 6.847 | See | See |
| 34 | KNeighborsClassifier_kd_tree | predict | 1000 | 1000 | 2 | 0.019 | 0.000 | 0.001 | 0.000 | 1 | 1 | 0.000 | 0.000 | 48.782 | 48.882 | See | See |
| 35 | KNeighborsClassifier_kd_tree | predict | 1000 | 1 | 2 | 0.001 | 0.000 | 0.000 | 0.001 | 1 | 1 | 0.000 | 0.000 | 6.646 | 6.986 | See | See |
KMeans_tall¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=3, max_iter=30, n_init=1, tol=1e-16.
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.522 | 0.068 | 30 | 0.031 | 0.0 | random | 0.387 | 0.026 | 1.347 | 1.350 | See | See |
| 3 | KMeans_tall | fit | 1000000 | 1000000 | 2 | 0.573 | 0.015 | 30 | 0.028 | 0.0 | k-means++ | 0.415 | 0.025 | 1.380 | 1.383 | See | See |
| 6 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 5.674 | 0.117 | 30 | 0.141 | 0.0 | random | 2.730 | 0.021 | 2.078 | 2.078 | See | See |
| 9 | KMeans_tall | fit | 1000000 | 1000000 | 100 | 5.975 | 0.075 | 30 | 0.134 | 0.0 | k-means++ | 2.940 | 0.042 | 2.033 | 2.033 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.002 | 0.001 | 30 | 0.009 | 0.000 | random | 0.0 | 0.0 | 12.564 | 15.117 | See | See |
| 2 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 30 | 0.000 | 0.001 | random | 0.0 | 0.0 | 8.409 | 14.199 | See | See |
| 4 | KMeans_tall | predict | 1000000 | 1000 | 2 | 0.001 | 0.000 | 30 | 0.011 | 0.000 | k-means++ | 0.0 | 0.0 | 10.551 | 12.232 | See | See |
| 5 | KMeans_tall | predict | 1000000 | 1 | 2 | 0.001 | 0.000 | 30 | 0.000 | 0.001 | k-means++ | 0.0 | 0.0 | 14.770 | 15.672 | See | See |
| 7 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.001 | 30 | 0.398 | 0.000 | random | 0.0 | 0.0 | 8.033 | 8.745 | See | See |
| 8 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.001 | 0.000 | 30 | 0.001 | 0.001 | random | 0.0 | 0.0 | 14.183 | 14.639 | See | See |
| 10 | KMeans_tall | predict | 1000000 | 1000 | 100 | 0.002 | 0.000 | 30 | 0.474 | 0.000 | k-means++ | 0.0 | 0.0 | 6.212 | 6.720 | See | See |
| 11 | KMeans_tall | predict | 1000000 | 1 | 100 | 0.001 | 0.000 | 30 | 0.001 | 0.001 | k-means++ | 0.0 | 0.0 | 14.053 | 14.534 | See | See |
KMeans_short¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: algorithm=full, n_clusters=300, max_iter=20, n_init=1, tol=1e-16.
| estimator | function | diff_adjusted_rand_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | algorithm | init | max_iter | n_clusters | n_init | tol | adjusted_rand_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | adjusted_rand_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 0.001090 | 10000 | 1000 | 2 | 0.001832 | 0.000171 | 20 | 0.008733 | 0.000002 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.000126 | 0.000439 | 0.000045 | -0.000965 | 4.169565 | 4.191795 |
| 4 | KMeans_short | predict | 0.001995 | 10000 | 1000 | 2 | 0.001836 | 0.000140 | 20 | 0.008715 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.001245 | 0.000439 | 0.000055 | -0.000750 | 4.183997 | 4.217065 |
| 7 | KMeans_short | predict | 0.015034 | 10000 | 1000 | 100 | 0.002504 | 0.000215 | 20 | 0.319429 | 0.000003 | full | random | 20 | 300 | 1 | 1.000000e-16 | 0.278733 | 0.000941 | 0.000091 | 0.293767 | 2.661817 | 2.674256 |
| 10 | KMeans_short | predict | 0.060044 | 10000 | 1000 | 100 | 0.002421 | 0.000147 | 20 | 0.330457 | 0.000002 | full | k-means++ | 20 | 300 | 1 | 1.000000e-16 | 0.317011 | 0.000947 | 0.000111 | 0.256968 | 2.555925 | 2.573268 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | KMeans_short | fit | 10000 | 10000 | 2 | 0.075 | 0.001 | 20 | 0.002 | 0.0 | random | 0.026 | 0.002 | 2.882 | 2.888 | See | See |
| 3 | KMeans_short | fit | 10000 | 10000 | 2 | 0.218 | 0.003 | 20 | 0.001 | 0.0 | k-means++ | 0.080 | 0.000 | 2.705 | 2.705 | See | See |
| 6 | KMeans_short | fit | 10000 | 10000 | 100 | 0.199 | 0.003 | 20 | 0.040 | 0.0 | random | 0.107 | 0.002 | 1.853 | 1.854 | See | See |
| 9 | KMeans_short | fit | 10000 | 10000 | 100 | 0.568 | 0.015 | 20 | 0.014 | 0.0 | k-means++ | 0.295 | 0.003 | 1.925 | 1.926 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | init | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.009 | 0.000 | random | 0.000 | 0.0 | 4.170 | 4.192 | See | See |
| 2 | KMeans_short | predict | 10000 | 1 | 2 | 0.001 | 0.0 | 20 | 0.000 | 0.001 | random | 0.000 | 0.0 | 14.039 | 14.482 | See | See |
| 4 | KMeans_short | predict | 10000 | 1000 | 2 | 0.002 | 0.0 | 20 | 0.009 | 0.000 | k-means++ | 0.000 | 0.0 | 4.184 | 4.217 | See | See |
| 5 | KMeans_short | predict | 10000 | 1 | 2 | 0.001 | 0.0 | 20 | 0.000 | 0.001 | k-means++ | 0.000 | 0.0 | 12.624 | 13.016 | See | See |
| 7 | KMeans_short | predict | 10000 | 1000 | 100 | 0.003 | 0.0 | 20 | 0.319 | 0.000 | random | 0.001 | 0.0 | 2.662 | 2.674 | See | See |
| 8 | KMeans_short | predict | 10000 | 1 | 100 | 0.001 | 0.0 | 20 | 0.001 | 0.001 | random | 0.000 | 0.0 | 10.472 | 10.782 | See | See |
| 10 | KMeans_short | predict | 10000 | 1000 | 100 | 0.002 | 0.0 | 20 | 0.330 | 0.000 | k-means++ | 0.001 | 0.0 | 2.556 | 2.573 | See | See |
| 11 | KMeans_short | predict | 10000 | 1 | 100 | 0.001 | 0.0 | 20 | 0.001 | 0.001 | k-means++ | 0.000 | 0.0 | 9.763 | 10.048 | See | See |
LogisticRegression¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: penalty=l2, dual=False, tol=0.0001, C=1.0, fit_intercept=True, intercept_scaling=1, class_weight=nan, random_state=nan, solver=lbfgs, max_iter=100, multi_class=auto, verbose=0, warm_start=False, n_jobs=nan, l1_ratio=nan.
| estimator | function | diff_accuracy_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | C | class_weight | dual | fit_intercept | intercept_scaling | l1_ratio | max_iter | multi_class | n_jobs | penalty | random_state | solver | tol | verbose | warm_start | accuracy_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | accuracy_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 0.01 | 1000000 | 1000 | 100 | 0.000395 | 0.000467 | [20] | 2.026996 | 3.946728e-07 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.56 | 0.000810 | 0.001551 | 0.55 | 0.486988 | 1.051396 |
| 4 | LogisticRegression | predict | 0.07 | 1000 | 100 | 10000 | 0.001595 | 0.000377 | [26] | 5.017054 | 1.594561e-05 | 1.0 | NaN | False | True | 1 | NaN | 100 | auto | NaN | l2 | NaN | lbfgs | 0.0001 | 0 | False | 0.35 | 0.005511 | 0.000775 | 0.28 | 0.289352 | 0.292203 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | LogisticRegression | fit | 1000000 | 1000000 | 100 | 11.187 | 0.433 | [20] | 0.072 | 0.000 | 2.021 | 0.011 | 5.534 | 5.534 | See | See |
| 3 | LogisticRegression | fit | 1000 | 1000 | 10000 | 0.994 | 0.603 | [26] | 0.081 | 0.001 | 1.002 | 0.032 | 0.991 | 0.992 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | LogisticRegression | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | [20] | 2.027 | 0.0 | 0.001 | 0.002 | 0.487 | 1.051 | See | See |
| 2 | LogisticRegression | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | [20] | 0.016 | 0.0 | 0.000 | 0.000 | 0.368 | 0.374 | See | See |
| 4 | LogisticRegression | predict | 1000 | 100 | 10000 | 0.002 | 0.0 | [26] | 5.017 | 0.0 | 0.006 | 0.001 | 0.289 | 0.292 | See | See |
| 5 | LogisticRegression | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | [26] | 1.129 | 0.0 | 0.002 | 0.000 | 0.045 | 0.045 | See | See |
Ridge¶scikit-learn-intelex (2021.20210705.191215) vs. scikit-learn (1.0.dev0)
All estimators share the following parameters: alpha=1.0, fit_intercept=True, normalize=deprecated, copy_X=True, max_iter=nan, tol=0.001, solver=auto, random_state=nan.
| estimator | function | diff_r2_scores | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | n_iter | iteration_throughput | latency | alpha | copy_X | fit_intercept | max_iter | normalize | random_state | solver | tol | r2_score_sklearn | mean_duration_sklearnex | std_duration_sklearnex | r2_score_sklearnex | speedup | std_speedup | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 0.039624 | 1000 | 1000 | 10000 | 0.01181 | 0.000205 | NaN | 6.773758 | 0.000012 | 1.0 | True | True | NaN | deprecated | NaN | auto | 0.001 | 0.082567 | 0.019658 | 0.000445 | 0.122191 | 0.600778 | 0.600931 |
fit
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 0 | Ridge | fit | 1000 | 1000 | 10000 | 0.181 | 0.012 | 0.443 | 0.0 | 0.184 | 0.002 | 0.981 | 0.981 | See | See |
| 3 | Ridge | fit | 1000000 | 1000000 | 100 | 1.176 | 0.096 | 0.680 | 0.0 | 0.311 | 0.247 | 3.781 | 4.828 | See | See |
predict
| estimator | function | n_samples_train | n_samples | n_features | mean_duration_sklearn | std_duration_sklearn | iteration_throughput | latency | mean_duration_sklearnex | std_duration_sklearnex | speedup | std_speedup | sklearn_profiling | sklearnex_profiling | |
|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|---|
| 1 | Ridge | predict | 1000 | 1000 | 10000 | 0.012 | 0.0 | 6.774 | 0.0 | 0.02 | 0.0 | 0.601 | 0.601 | See | See |
| 2 | Ridge | predict | 1000 | 1 | 10000 | 0.000 | 0.0 | 1.354 | 0.0 | 0.00 | 0.0 | 0.650 | 0.717 | See | See |
| 4 | Ridge | predict | 1000000 | 1000 | 100 | 0.000 | 0.0 | 5.310 | 0.0 | 0.00 | 0.0 | 0.566 | 0.800 | See | See |
| 5 | Ridge | predict | 1000000 | 1 | 100 | 0.000 | 0.0 | 0.016 | 0.0 | 0.00 | 0.0 | 0.651 | 0.685 | See | See |